Our approach consists of two main components that interact in different stages of the learning pipeline: First, SkiROS [1]}, a skill-based framework for ROS, which represents the implemented skills with BTs, hosts the world model (digital twin), and interacts with the planner. SkiROS is also used to execute BTs while learning and to perform tasks on the real system. Second, the learning framework that provides the simulation, the integration with the policy optimizer as well as the reward function definition and calculation.
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